Computational Molecular Science

Machine-learning methods for molecular states, rare events, and kinetics.

I develop interpretable simulation and data-driven methods for identifying molecular states, generating transition pathways, and estimating kinetics from molecular dynamics.

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Ph.D. Thesis Submitted · Available for Postdoctoral Positions from Late 2026
Free-energy landscape showing metastable basins and rare-event transition pathway

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Selected Publications

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Ph.D. thesis submitted. Available for postdoctoral positions from Late 2026.

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Research Case Studies

Postdoctoral Research Fit & Future Directions

Focusing on three core computational programmes connecting previous Ph.D. foundations to future host laboratory directions:

Publications & Preprints

Scientific Software

About & Academic Background

Portrait of Dibyendu Maity

Dibyendu Maity

Computational Biophysicist

S. N. Bose National Centre for Basic Sciences, Kolkata

Research Statement

I develop interpretable, physics-grounded computational methods at the intersection of molecular dynamics, enhanced sampling, and machine learning. My work addresses a recurring bottleneck in molecular simulation: bridging the gap between the femtosecond timestep of atomic forces and the micro- to millisecond timescales at which biologically and chemically relevant events — conformational changes, nucleation, ligand binding — actually occur.

During my Ph.D., I built methods that accelerate this process from both ends: representation learning to identify reaction coordinates and structural phases directly from trajectory data (IceCoder), adaptive sampling to steer short parallel simulations toward rare transition pathways (PathGennie, TRAILS-MD), and kinetics estimation through weighted-ensemble resampling with temporal coherence (CoWERA).

I am motivated by problems where data-driven models must respect physical symmetries, conservation laws, and thermodynamic consistency — not just minimise loss functions. My postdoctoral research vision focuses on physics-aware molecular representation learning, scalable adaptive sampling for drug discovery, and trajectory-resolved kinetics for complex biomolecular systems.

Research Interests

Molecular Dynamics Enhanced Sampling Rare-Event Methods Machine Learning for Chemistry Graph Neural Networks Variational Autoencoders Structural Phase Identification Weighted-Ensemble Methods Free-Energy Calculations SOAP Descriptors Reaction Coordinates Protein Folding

Education

2021 – 2026

Ph.D. in Physics (Theoretical)

University of Calcutta / S. N. Bose National Centre for Basic Sciences, Kolkata

Thesis: Development and Application of Machine Learning Approaches for Prediction, Identification and Sampling Problems in the Field of Molecular Modeling and Simulation

Advisor: Prof. Suman Chakrabarty

Thesis Submitted
2019 – 2021

M.Sc. in Physical Sciences

University of Calcutta / S. N. Bose National Centre for Basic Sciences, Kolkata

Integrated Ph.D. Programme · First Class · 79.80%

2016 – 2019

B.Sc. in Physics (Honours)

Midnapore College (Autonomous), West Bengal

First Class Honours in Physics · 81.25%

2014 – 2016

Higher Secondary and Secondary

Ananda Nagar Srinath Vidyapith, Anandanagar

Higher Secondary (WBCHSE), 2016 · 94.0%

Secondary (WBBSE), 2014 · 94.43%

Conference Presentations & Invited Talks

  1. Poster Presentation, Poster Award - Computational and Data-Driven Advanced Materials (CDAM 2026), CSIR-Central Glass and Ceramic Research Institute, Kolkata, 7-8 April 2026.
  2. Poster Presentation and Lightning Talk - Workshop on Machine Learning, Enhanced Sampling, and Dynamical Surrogate Models for Glassy and Adaptable Materials, University of Chicago Center in Delhi, New Delhi, 30 March-1 April 2026.
  3. Poster Presentation - Biophysics Today, S. N. Bose National Centre for Basic Sciences, Kolkata, 2-4 December 2025.
  4. Poster Presentation - Recent Advances in Modeling Rare Events (RARE 2025), Khajuraho, 9-12 March 2025.
  5. Invited Lecture - Supramolecular Chemistry Discussion 2024, IISER Kolkata, 8 December 2024.
  6. Poster Presentation and Lightning Talk - CHEMDOJO 3.0, 1-4 October 2024.
  7. Poster Presentation, Best Poster Award - JNCASR-CECAM Conference: MD@60, Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, 26-29 February 2024.
  8. Poster Presentation, Lightning Talk, and Hackathon - ML4MS2024, Thiruvananthapuram, 1-4 February 2024.
  9. Poster Presentation - Theoretical Chemistry Symposium 2023 (TCS-2023), Indian Institute of Technology Madras, Chennai, 7-10 December 2023.
  10. Poster Presentation - Physical Chemistry Symposium 2023 (SoPhyC-2023), Indian Institute of Technology Kanpur, 29-31 October 2023.
  11. Poster Presentation, Best Poster Award - RAC-TCA 2022, NIT Meghalaya and North-Eastern Hill University, 18-20 November 2022.

Awards & Recognition

  • INSPIRE Scholarship for Higher Education (SHE) - Department of Science and Technology, Government of India, 2016-2019; awarded under the INSPIRE programme for students within the top 1% of the WBCHSE board examination.
  • GATE 2021 - Physics - Qualified with All India Rank 177.
  • National Graduate Physics Examination (NGPE) - Recognized among the national top 26 students in NGPE-2019.
  • JEST 2019 - Physics - Qualified with All India Rank 191.
  • IIT JAM 2019 - Physics - Qualified with All India Rank 898.

Contact & Collaboration

I am actively seeking postdoctoral positions in computational molecular science, molecular simulation, and machine learning for chemistry. Please reach out for research discussions, collaboration, or opportunities.

Email

dibyendumaity1999@gmail.com

Google Scholar

Research profile and publications

GitHub

dmighty007 · TeamSuman

Contact Details

Phone: 8158055918

Email: dibyendumaity1999@gmail.com

Institutional email: dibyendumaity1999@bose.res.in

Address: Anikola, Dantan, Paschim Medinipur, West Bengal 721457, India